Media Claude Skills
3 032 media skills from 496 authors. They create and process images, video and sound. Half of them fit into 1 962 tokens or less — that is what one costs your context window when the agent loads it. 771 ship runnable scripts rather than instructions alone. 30 of them cannot work without an MCP server, most often rube. We also found 347 copies of these same skills sitting in other people's repositories — counted once here, not 347 times.
3 032 unique 496 authors 13 updated this month 173 from vendors
Build Z-Image txt2img workflows — RedCraft checkpoint, Z-Image Turbo/Base LoRAs, ControlNet, and sampler presets
Draft a LinkedIn comment on someone else's post from its URL, or reshare (repost) it to your feed with optional commentary. Use when the user pastes a post URL and asks to comment, engage, be first commenter, or repost with their thoughts. Produces 1-3 variants in the user's voice, picks a reaction, and publishes via Publora on approval. Not for replying to existing comments (use linkedin-reply-handler).
Repurpose existing content into a native LinkedIn post. Take a tweet, thread, YouTube video, blog, or newsletter and rebuild it for LinkedIn: re-hook before the fold, expand to the 900 to 1300 char sweet spot, add whitespace and a CTA, move links to the first comment, run the humanizer, publish via Publora on approval. Not for writing from scratch (use linkedin-post-writer), not for auditing a draft (use linkedin-humanizer --mode audit).
Audit and rewrite a LinkedIn profile end-to-end for 2026: headline, About 7-step, Featured, banner, photo, Experience metrics, Skills, custom URL, recommendations. Triggers on "review my profile", "rewrite my headline", "fix my About", "optimize banner", "profile audit", "LinkedIn bio". Converts resume-style profiles to ones that convert 3-5x better.
| Distills ANY messy input — brain dump, transcript, long PRD, stakeholder notes, feature request, voice memo — into a tight five-field SPEC.md kernel that any Constraints, Non-Goals, Success Metrics. Use when the user says "create a spec", "write a spec for", "distill this into a spec", "I have a brain dump", "turn this into something structured", "clean up these notes", "make a SPEC from", "I want to define the problem", "help me scope this", "summarize what we're building", "I have a PRD but need a kernel", "what are we actually solving?", or drops raw text/transcript and asks for structure. Also use when starting any new initiative and a clean shared definition is missing.
公众号运营｜微信公众号｜公众号一条龙｜公众号全流程｜自媒体运营｜wechat automation｜content pipeline｜AIGC workflow — 公众号一条龙运营总控入口，选题→写稿→审稿→排版→配图→发布串联 8 个子 skill，单条指令完成整篇图文从 0 到上架。面向公众号小编、自媒体、品牌内容。触发词分层：**一条龙流程**「一条龙」「完整流程」「从头做」「从 0 到发布」；**新做新发**「帮我写篇公众号文章」「做一篇公众号文章」「我想发一篇」「帮我发一篇」「再来一篇」；**选题起点**「今天写什么好」「有什么好写的」「找个话题」「爆款选题」「热点选题」「起个爆款标题」；**策划起点**「内容日历」「系列策划」「专栏规划」「连载」；**流程恢复**「接着上次那篇」「继续昨天的」「继续上次的」「接着之前的进度」；**显式模型新写**「用 GPT 写一篇」「用 DeepSeek 写一篇」「把提纲写成文章」。子 skill（topics/writing/review/formatting/images/publish/sticker/assets）单独触发仅限对**已有产物**的修改场景（如"改标题""润色这段""排版""审稿""加封面""发布"）；新做/策划/多环节串联一律走本入口。
公众号素材｜业务资料库｜预设包｜.aws 预设包｜主题包｜品牌包｜aiworkskills.cn — 用户业务资料库与预设包管理：业务资料按产品名组织在 `.aws-article/products/{产品名}/`（介绍 .md 直挂产品根 + 配图归 `images/` 子目录含同名说明 .md），AI 与用户对话产出业务介绍内容时引导用户保存；图片入库走 `product_image_ingest.py --product <产品名> --stem <中文名>`。导入 .aws ZIP 预设包（本地文件或 `https://aiworkskills.cn/**/*.aws` URL）合并主题/配色/字体配置到 `.aws-article/presets/`；`config.yaml` 仅本地不存在时从包内复制，已存在则 stdout 输出差异 JSON 不覆盖。面向内容运营、品牌团队、设计支持岗。触发词：「素材库入库」「stock images」「上传图到素材库」「.aws」「预设包」「导入预设」「主题包」「aiworkskills.cn 链接」「.aws 下载地址」。
公众号封面｜公众号配图｜公众号插图｜AI 生图 — 公众号 AI 封面与配图生成，按文章标题与内容自动匹配画风，一稿多方案，多风格预设可复用。面向公众号编辑、自媒体、品牌设计。触发词：「封面」「配图」「插图」「生成图片」「给文章加图」「做个封面」「文章插图」「配个图」。不写正文只发一组图请走 aws-wechat-sticker；需要多环节串联（写+审+排+配图+发）请走 aws-wechat-article-main。
公众号贴图｜九宫格｜多图推送｜图片消息｜表情包 — 贴图与多图推送：从创意构思、AI 生图到公众号图片消息发布全流程，含九宫格自动排布、多图压缩、组图打包。面向公众号运营、自媒体、IP 账号。触发词：「贴图」「多图推送」「发组图」「图片消息」「九宫格」「做一组图」「图片帖子」「发几张图」「不写正文发图」「只发图不写字」。是文章内配图/封面请走 aws-wechat-article-images；需要多环节串联（写+审+排+配图+发）请走 aws-wechat-article-main。
独立校验与审查文件系统短剧项目中的故事、剧本、资产、连续性、资产图片提示词、分镜、关键帧和视频提示词。用户提出“审稿/检查剧本”“检查资产或连续性”“检查图片/视频提示词”“审查或诊断模板感”，或判断一集能否交付文本或 JSON 时使用；只发布审查问题、审查结论和修订要求，不代替负责人修改来源文件。
为已接受的短剧镜头和关键帧编写或修改可复制的通用视频提示词与运动规格。用户提到视频提示词、文生视频、图生视频动作、人物表演过程、运镜、对白口型、环境运动、镜头时长、起止状态或把分镜转成视频提示词时直接使用；只描述单个已编镜头内的运动、表演、摄影与声音，不生成视频，不调用模型或供应商接口，也不改写分镜边界。
从短剧剧本拆解并统筹角色/造型、场景/视图、道具/状态和跨场连续性。用户说‘拆角色/场景/道具’、‘做资产表/角色表/场景表/道具表’、‘判断复用还是新变体’、‘更新造型/道具状态’，或拿现成剧本直接做视觉资产准备时使用；本 skill 不写资产图提示词，也不生成图片或视频。
为已确认的短剧角色、造型、场景、视角、道具和状态编写或修改可复制的通用资产图片提示词。用户提到角色设定图、三视图、人物参考图、场景设定图、场景空镜、场景板、道具图、造型或状态变体、局部编辑提示词，或要求用自然语言修改现有图片提示词时直接使用；只产出结构化规格与 Markdown 文本，不生成图片，也不调用模型或供应商接口。
Use this skill to fix scroll jank, lost item state, and broken animateItem() animations in LazyColumn, LazyRow, LazyVerticalGrid, and LazyHorizontalGrid. Covers stable item keys, contentType for mixed-type feeds, Modifier.animateItem() requirements, hoisting modifier chains and painters out of the items lambda, and validating item composable stability. Use when the developer mentions LazyColumn jank, dropped frames while scrolling, items losing scroll state on insert/remove/reorder, mixed feeds of cards/headers/ads feeling sluggish, animateItem() not animating, RecyclerView view-type analog, key parameter, or contentType parameter. The prefetch-window tuning lives in a sibling skill.
Use this skill to push frequently-changing Jetpack Compose state reads (scroll position, animation values, drag offsets) out of the Composition phase and down into Layout or Draw using lambda-based modifiers like Modifier.offset { }, Modifier.layout { }, Modifier.graphicsLayer { }, Modifier.drawBehind { }, and Modifier.drawWithCache { }. Covers the three-phase model (Composition, Layout, Draw), why a state read at phase N invalidates phase N and every phase below, the modifier-phase cheat sheet, and lambda providers (() -> T) for hoisting hot values across composables. Use when the developer mentions every-frame work, scroll jank, animation jank, dropped frames, animated alpha or offset, "the whole subtree recomposes on scroll", Modifier.alpha(state.value), Modifier.offset(x.dp), or graphicsLayer.
Speak the last response aloud using text-to-speech
Stop any currently playing text-to-speech audio
Enable auto TTS for this session
Disable auto TTS for this session
Use when writing or reviewing Python code in this repo that calls Deepgram audio analytics overlays on `/v1/listen` - summarize, topics, intents, sentiment, diarize, redact, detect_language, entity detection. Same endpoint as plain STT but with analytics params. Covers both REST (`client.listen.v1.media.transcribe_url`/`transcribe_file`) and the WSS-supported subset (`client.listen.v1.connect`). Use `deepgram-python-speech-to-text` for plain transcription, `deepgram-python-text-intelligence` for analytics on already-transcribed text. Triggers include "diarize", "summarize audio", "sentiment from audio", "redact PII", "topic detection audio", "audio intelligence", "detect language audio".
Use when writing or reviewing Python code in this repo that builds an interactive voice agent via `agent.deepgram.com/v1/agent/converse`. Covers `client.agent.v1.connect()`, `AgentV1Settings`, `send_settings`, `send_media`, event handling, and function/tool calling. Full-duplex STT + LLM + TTS with barge-in. Use `deepgram-python-text-to-speech` for one-way synthesis, `deepgram-python-speech-to-text` / `deepgram-python-conversational-stt` for transcription only. Triggers include "voice agent", "agent converse", "full duplex", "interactive assistant", "barge-in", "agent.v1", "function calling", "AgentV1Settings".
Use when writing or reviewing Python code in this repo that calls Deepgram Text-to-Speech v1 (`/v1/speak`) for audio synthesis. Covers one-shot REST (`client.speak.v1.audio.generate`) and streaming WebSocket (`client.speak.v1.connect`). Also covers the in-repo `deepgram.helpers.TextBuilder` for incremental text assembly before synthesis. Use `deepgram-python-voice-agent` when you need full-duplex STT + LLM + TTS with barge-in. Triggers include "TTS", "speak", "synthesize voice", "aura", "text to speech", "speak.v1", "TextBuilder".
Use when writing or reviewing Python code in this repo that calls Deepgram Speech-to-Text v1 (`/v1/listen`) for prerecorded or live audio transcription. Covers `client.listen.v1.media.transcribe_url` / `transcribe_file` (REST) and `client.listen.v1.connect` (WebSocket). Use this skill for basic ASR; use `deepgram-python-audio-intelligence` for summarize/sentiment/topics/diarize overlays, `deepgram-python-conversational-stt` for turn-taking v2/Flux, and `deepgram-python-voice-agent` for full-duplex assistants. Triggers include "transcribe", "live transcription", "speech to text", "STT", "listen endpoint", "nova-3", "listen.v1".
Use when writing or reviewing Python code in this repo that calls Deepgram Conversational STT v2 / Flux (`/v2/listen`) for turn-aware streaming transcription. Covers `client.listen.v2.connect(...)`, Flux models, end-of-turn detection. Use `deepgram-python-speech-to-text` for standard v1 ASR, `deepgram-python-voice-agent` for full-duplex interactive assistants. Triggers include "flux", "v2 listen", "conversational STT", "turn detection", "end of turn", "EOT", "listen.v2", "flux-general-en", "flux-general-multi".
> Generate and improve accessible alt text for data visualizations and images in R packages and Quarto documents. Use when the user wants to add, improve, or audit alt text for figures in a pkgdown site or .qmd files. Activate for requests that mention fig-alt, fig.alt, figure descriptions, or alt text in the context of an R package or Quarto document.
> Customer leadership advisor on CX strategy, retention and expansion, and voice-of-customer programs. Use when defining a CX strategy, scoring CX maturity, planning churn interventions, or designing a VoC program.
> Audit PowerPoint (.pptx) decks for slide count, text density, embedded images and fonts, hidden slides, speaker notes, and animation density. Use when reviewing a board deck, sales deck, or conference talk before sending.
> typography, color, and cross-channel consistency. Use when creating style guides, defining brand voice, auditing brand consistency, or setting visual standards.
> This skill should be used when the user asks to "plan video content", "create a video calendar", "optimize video SEO", "analyze thumbnail performance", "improve video titles", "schedule video production", or "build a YouTube strategy".
Image processing skill for cropping images to 50% from center and rotating them 90 degrees clockwise. This skill should be used when users request image cropping to center, image rotation, or both operations combined on image files.
When you want to read and extract structured notes from a book — PDF, EPUB, MOBI, markdown, .txt, pasted text, or URL to a public-domain work. Reads in chunks (by chapter when a TOC exists, by 50-page blocks otherwise), extracts per-chapter TL;DR + key concepts + quotes + action items + frameworks, and offers to capture to second-brain raw/ as a highlights- file. Four modes — notes (default, chapter-by-chapter), summary (whole-book TL;DR + 3–5 takeaways), quotes (pull-quote highlights only), study (notes + Q&A spaced-rep prep). Triggers on "/read-book," "read this book," "extract notes from this PDF," "what's in this book," "summarize this ebook," "pull quotes from this." Sibling to watch-video (same content-consumption pattern, different medium).
When you want to create, adapt, or update a Claude Code skill in one of your sibling repos (list your own repos in ~/.config/makerskills/skillify/repos.yaml; defaults to makerskills). Routes to the right mode automatically. Modes — CREATE (from-chat / from-video / from-dump / from-scratch) turns a workflow, brief, recording, or fresh idea into a new skill. ADAPT ports an external skill (GitHub URL, agentskills.io, local disk) into your namespace with three-bucket classification (keep/adapt/add) + license check + attribution. UPDATE improves existing skills from learnings with cross-skill propagation, memory-vs-skill triage, and semver discipline. Defers to Anthropic's guidance (compound-engineering:create-agent-skill, compound-engineering:skill-creator, compound-engineering:heal-skill) for schema and best-practice depth. Triggers on "/skillify," "create a skill," "make this a skill," "skill from this chat," "extract a skill from what we've been doing," "adapt this skill," "port this skill," "fork this skill," "borrow this skill," "update X skill," "apply this to the relevant skills," "propagate this learning," "improve [skill]," "fix [skill]," "iterate on [skill]." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code.
When you want to extract content from a video — YouTube, Loom, Vimeo, Riverside, Zoom recording, local MP4, X/IG video, anything yt-dlp supports. Three depth modes user picks per invocation — transcript (just words, fast/free), visual (transcript + ffmpeg frame extraction + Claude vision pass on key moments), multimodal (Gemini native video ingestion if $GEMINI_API_KEY set, else dense Claude vision). Uses MLX-Whisper local on Mac for transcription, falls back to platform-provided transcripts when available (Loom, Riverside, YouTube auto-subs). Saves to ~/Documents/videos/<source>-<slug>-<date>/ and optionally captures summary to second-brain raw/ as call-/meeting-/note-. Triggers on "/watch-video <url>," "watch this video," "transcribe this loom," "analyze this video," "summarize this recording," "key moments from this," "what happened in this video." This skill replaces and broadens the prior youtube-transcript skill.
> 把长视频按 Agent 选择的原片区间剪成短片。作为两阶段创作流程中的剪辑环节，读取 clip_plan.json 与源视频， 输出 edited_source.mp4；随后 Agent 按输出时间线写 narration.json。单独调用且未传 --no-narration-map 时， 仍支持旧版单阶段路径，把原片时间的 narration.json 映射为 narration_mapped.json。 触发词：视频剪辑、剪辑式解说、video cut、clip plan、拼剪。
> 把带时间戳的 narration.json 合成为中文解说音频。使用 MiMo TTS（mimo-v2.5-tts）逐段生成语音， 按时间窗动态适配语速并处理响度；输入输出时间线上的旁白，产出 tts_segments 与 tts_meta.json。 旧版直接剪辑路径也可显式传入 narration_mapped.json。触发词：配音、语音合成、TTS、解说配音、 voiceover、text to speech、旁白配音。
> 对已完成分析的视频进行导演与剪辑策划，再写带时间戳的中文解说并校验。work_dir 已包含 agent_narration_brief.md 与 vlm_analysis.json 时使用。适用于故事方向、片段选择、画面/原声/旁白分工、 解说写作与复核。输入 work_dir 中的理解索引；输出 recap_story_plan.json、visual_audio_board.json、 cut 模式需要的 clip_plan.json，以及通过校验的 narration.json。触发词：解说词、写解说、视频旁白、 narration script、写稿、解说文案、剪辑思路、导演思路。
> 合成视频解说最终成片：把旁白音频铺到源视频上，按旁白窗口压低原声，生成 SRT / ASS 字幕并可烧录， 最后做响度标准化。作为最终合成阶段使用。输入源视频、tts_meta.json 与旁白位置； 输出 recap 成片和字幕。触发词：视频合成、混音、字幕、压字幕、assemble video、mux、ducking、subtitles、成片。
> 从输入视频端到端生成中文解说成片。用户提供 .mp4 / .mov / .mkv / .webm，并要求添加旁白、 配音、总结、短剧/电视剧/电影/纪录片/科普解说时使用。负责编排 video-* 技能链：视频理解 → Agent 制定故事与视听方案 → 剪辑 → 配音 → 合成。触发词：视频解说、视频旁白、生成解说、 视频 recap、video recap、voiceover、narration、auto-dub、recap。
国内自媒体发布前风险自审与保意修复：审口播稿、文章、图文笔记、字幕、封面文字能不能发抖音/小红书/微信视频号，给出具体位置、依据和可直接替换的改稿；被限流/删除/处罚后帮你复盘归因；你的行业敏感词、误报白名单和踩坑案例会沉淀成个人规则库，越用越准。Use when 用户说"能不能发""审一下稿子""查违禁词/敏感词""会不会限流/被限流了""帮我改成能发的版本""发布前检查""被平台处罚/删除了""帮我盯着这个词""导入违禁词表"。Not for 海外平台(X/YouTube)内容审核、起号涨粉策略、写稿创作本身。
Create, edit, caption, voice, assemble, validate, and export editable video timelines with Timeline Studio. Use for automatic video editing, AI voiceover videos, subtitle generation, image-to-video assembly, short-form video production, deterministic local video rendering, .timeline project automation, or end-to-end editor evaluation in Codex, Claude Code, Copilot, and Gemini CLI.
This skill should be used whenever users need YouTube video scripts written. On first use, collects comprehensive preferences including script type, tone, target audience, style, video length, hook style, use of humor, personality, and storytelling approach. Generates complete, production-ready YouTube scripts tailored to user's specifications for any topic. Maintains database of preferences and past scripts for consistent style.
AI image generation: Gemini and Nano Banana backends; single/series/batch workflows with prompt-to-disk.
Create voice profiles from writing samples.
FFmpeg-based video creation from image and audio.
Video editing pipeline: cut footage, assemble clips via FFmpeg and Remotion.
| Unified voice content generation pipeline with mandatory validation and HOOK-GATE, VALIDATE, REFINE, VARIETY-GATE, JOY-CHECK, ANTI-AI, CLOSE-GATE, OUTPUT, CLEANUP. Use when writing articles, blog posts, or any content that uses a voice profile. Use for "write article", "blog post", "write in voice", "generate content", "draft article", "write about".
Critique-and-rewrite loop for voice fidelity validation.
AI sprite generation: portraits, idle loops, animated sheets via Codex/Nano Banana. Per-row generation, animation presets, video-to-sprite, identity lock. Use for generated character art.